Evolutionary design of pseudorandom sequence generators based on cellular automata and its applicability in current cryptosystems

摘要

In this work, a genetic algorithm is used to find cellular automata rules that make cellular automata behave like good pseudorandom sequence generators. Pseudorandom sequence generators based on one-dimensional cellular automata with non-homogeneous rules and arbitrary neighbors are proposed. The fitness function combines entropy measures and standard statistical tests for random sequences. The generators found are statistically compared to some well-known pseudorandom sequences generators.